===================
## [1] "time" "latitude" "longitude" "depth" "mag"
## [6] "magType" "nst" "gap" "dmin" "rms"
## [11] "net" "id" "updated" "place" "type"
##
## deep intermediate shallow surface
## 91 126 1090 11
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 7.000 7.100 7.200 7.358 7.600 9.600
##
## class1 class2 class3 class4 class5 class6
## 885 341 75 13 3 1
##
## 1900s 1910s 1920s 1930s 1940s 1950s 1960s 1970s 1980s 1990 2000s 2010s
## 30 60 112 126 110 101 139 131 110 155 148 96
## [1] "time" "latitude" "longitude" "depth" "mag"
## [6] "magType" "nst" "gap" "dmin" "rms"
## [11] "net" "id" "updated" "place" "type"
## [16] "New_Time" "Date" "Time" "Year" "Month"
## [21] "Day" "Hour" "depth_class" "mag_class" "long"
## [26] "long_class" "lat_class" "decade"
## 'data.frame': 1318 obs. of 28 variables:
## $ time : Factor w/ 1318 levels "1900-07-29T06:59:00.000Z",..: 546 592 1252 1150 468 1226 605 1272 396 442 ...
## $ latitude : num -38.14 60.91 38.3 3.29 52.62 ...
## $ longitude : num -73.4 -147.3 142.4 96 159.8 ...
## $ depth : num 25 25 29 30 21.6 22.9 30.3 20 15 15 ...
## $ mag : num 9.6 9.3 9 9 8.9 8.8 8.7 8.6 8.6 8.6 ...
## $ magType : Factor w/ 6 levels "","ms","mw","mwb",..: 3 3 6 5 3 5 3 6 3 3 ...
## $ nst : int NA NA 541 601 NA 454 NA 499 NA NA ...
## $ gap : num NA NA 9.5 22 NA 17.8 NA 16.6 NA NA ...
## $ dmin : num NA NA NA NA NA NA NA NA NA NA ...
## $ rms : num NA NA 1.16 1.17 NA 1.09 NA 1.33 NA NA ...
## $ net : Factor w/ 4 levels "atlas","gcmt",..: 3 3 4 4 3 4 3 4 3 3 ...
## $ id : Factor w/ 1318 levels "atlas19230901025800",..: 240 207 1287 1188 322 1261 193 1306 381 338 ...
## $ updated : Factor w/ 1296 levels "2014-02-11T02:25:27.101Z",..: 160 631 1217 1168 40 1218 219 1222 572 549 ...
## $ place : Factor w/ 364 levels "101km SW of Atka, Alaska",..: 52 315 181 236 234 239 270 236 297 89 ...
## $ type : Factor w/ 1 level "earthquake": 1 1 1 1 1 1 1 1 1 1 ...
## $ New_Time : chr "1960-05-22 19:11:20.000" "1964-03-28 03:36:16.000" "2011-03-11 05:46:24.120" "2004-12-26 00:58:53.450" ...
## $ Date : Date, format: "1960-05-22" "1964-03-28" ...
## $ Time : chr "19:11:20" "03:36:16" "05:46:24" "00:58:53" ...
## $ Year : num 1960 1964 2011 2004 1952 ...
## $ Month : num 5 3 3 12 11 2 2 4 4 8 ...
## $ Day : num 22 28 11 26 4 27 4 11 1 15 ...
## $ Hour : num 19 3 5 0 16 6 5 8 12 14 ...
## $ depth_class: chr "shallow" "shallow" "shallow" "shallow" ...
## $ mag_class : Factor w/ 6 levels "class1","class2",..: 6 5 5 5 4 4 4 4 4 4 ...
## $ long : num 287 213 142 96 160 ...
## $ long_class : chr "WestH" "WestH" "EastH" "EastH" ...
## $ lat_class : chr "SouthH" "NorthH" "NorthH" "NorthH" ...
## $ decade : Factor w/ 12 levels "1900s","1910s",..: 7 7 12 11 6 12 7 12 5 6 ...
## Warning in loop_apply(n, do.ply): Stacking not well defined when ymin != 0
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 7.000 7.100 7.200 7.358 7.600 9.600
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.000 4.000 7.000 6.565 10.000 12.000
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 15.00 28.75 71.98 40.00 675.40
##
## 7 7.1 7.2 7.3 7.4 7.5 7.6 7.7 7.8 7.9 8 8.1 8.2 8.3 8.4 8.5 8.6 8.7
## 289 205 180 119 92 83 80 77 67 34 21 25 13 13 3 4 6 1
## 8.8 8.9 9 9.3 9.6
## 1 1 2 1 1
##
## 1 2 3 4 5 6 7 8 9 10 11 12
## 108 106 109 108 119 98 104 124 90 117 129 106
##
## 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
## 55 60 66 63 51 45 54 50 53 50 61 50 49 48 68 45 58 53 57 62 51 62 65 42
##
## EastH WestH
## 900 418
##
## NorthH SouthH
## 720 598
## Warning in loop_apply(n, do.ply): Removed 2 rows containing missing values
## (geom_path).
## Warning in loop_apply(n, do.ply): Removed 2 rows containing missing values
## (geom_path).
## Warning in loop_apply(n, do.ply): Removed 2 rows containing missing values
## (geom_path).
## Warning in loop_apply(n, do.ply): Removed 2 rows containing missing values
## (geom_path).
## Warning in loop_apply(n, do.ply): Removed 2 rows containing missing values
## (geom_path).
## Warning in loop_apply(n, do.ply): Removed 2 rows containing missing values
## (geom_path).
##
## 1900s 1910s 1920s 1930s 1940s 1950s 1960s 1970s 1980s 1990 2000s 2010s
## 30 60 112 126 110 101 139 131 110 155 148 96
## ms mw mwb mwc mww
## 7 94 907 46 193 71
## atlas gcmt iscgem us
## 7 1 731 579
## Warning in loop_apply(n, do.ply): Removed 150 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 5 rows containing missing values
## (geom_point).
## Warning in loop_apply(n, do.ply): Removed 1 rows containing missing values
## (stat_smooth).
## Warning in loop_apply(n, do.ply): Removed 115 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 1 rows containing missing values
## (stat_summary).
## Warning in loop_apply(n, do.ply): Removed 109 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 247 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 145 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 110 rows containing missing
## values (stat_smooth).
## Warning in loop_apply(n, do.ply): Removed 110 rows containing missing
## values (stat_summary).
## Warning in loop_apply(n, do.ply): Removed 110 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 27 rows containing missing
## values (stat_summary).
## Warning in loop_apply(n, do.ply): Removed 27 rows containing missing
## values (stat_smooth).
## Warning in loop_apply(n, do.ply): Removed 27 rows containing missing
## values (geom_point).
##
## Pearson's product-moment correlation
##
## data: mag and depth
## t = -1.1972, df = 1316, p-value = 0.2315
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.08682423 0.02105088
## sample estimates:
## cor
## -0.03298273
##
## Pearson's product-moment correlation
##
## data: mag and depth
## t = -0.9579, df = 1099, p-value = 0.3383
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.08781253 0.03024934
## sample estimates:
## cor
## -0.02888232
##
## Pearson's product-moment correlation
##
## data: mag and depth
## t = -1.1972, df = 1316, p-value = 0.2315
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.08682423 0.02105088
## sample estimates:
## cor
## -0.03298273
##
## Pearson's product-moment correlation
##
## data: mag and depth
## t = 0.6564, df = 89, p-value = 0.5133
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.1385166 0.2714726
## sample estimates:
## cor
## 0.06940823
## Warning in loop_apply(n, do.ply): Removed 129 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 109 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 6 rows containing missing values
## (geom_point).
## Warning in loop_apply(n, do.ply): Removed 193 rows containing non-finite
## values (stat_boxplot).
## Warning in loop_apply(n, do.ply): Removed 193 rows containing missing
## values (stat_summary).
## Warning in loop_apply(n, do.ply): Removed 126 rows containing non-finite
## values (stat_boxplot).
## Warning in loop_apply(n, do.ply): Removed 126 rows containing missing
## values (stat_summary).
## Warning in loop_apply(n, do.ply): Removed 942 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 942 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 513 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 513 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 1098 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 1098 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 600 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 600 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 8 rows containing missing values
## (geom_path).
## Warning in loop_apply(n, do.ply): Removed 8 rows containing missing values
## (geom_path).
##
## Pearson's product-moment correlation
##
## data: mag and depth
## t = 0.4643, df = 187, p-value = 0.643
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.1093241 0.1758144
## sample estimates:
## cor
## 0.03393572
##
## Pearson's product-moment correlation
##
## data: mag and depth
## t = -0.2816, df = 529, p-value = 0.7783
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.09723304 0.07292208
## sample estimates:
## cor
## -0.01224412
## Warning in loop_apply(n, do.ply): Removed 17 rows containing missing
## values (geom_path).
## Warning in loop_apply(n, do.ply): Removed 17 rows containing missing
## values (geom_path).
##
## Pearson's product-moment correlation
##
## data: mag and depth
## t = -1.1841, df = 367, p-value = 0.2372
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.16275713 0.04065794
## sample estimates:
## cor
## -0.06169016
##
## Pearson's product-moment correlation
##
## data: mag and depth
## t = -1.0876, df = 227, p-value = 0.2779
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## -0.19977833 0.05818228
## sample estimates:
## cor
## -0.07200198
## Warning in loop_apply(n, do.ply): Removed 126 rows containing non-finite
## values (stat_boxplot).
## Warning in loop_apply(n, do.ply): Removed 126 rows containing missing
## values (stat_summary).
## Warning in loop_apply(n, do.ply): Removed 126 rows containing non-finite
## values (stat_boxplot).
## Warning in loop_apply(n, do.ply): Removed 126 rows containing missing
## values (stat_summary).
## Warning in loop_apply(n, do.ply): Removed 126 rows containing non-finite
## values (stat_boxplot).
## Warning in loop_apply(n, do.ply): Removed 126 rows containing missing
## values (stat_summary).